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Flooding protocols for wireless networks in general have been shown to be very inefficient and therefore are mainly used in network initialization or route discovery and maintenance. In this paper, we propose a framework of constrained flooding protocols. The framework incorporates a reinforcement learning kernel, a differential delay mechanism, and a constrained and probabilistic retransmission policy. This type of protocol takes the advantages of robustness from flooding, but maintains energy efficiency by constraining retransmissions. Without the use of any control packets, such a protocol adapts to the specific routing requirements of the task and the dynamic changes of the network. We analyze this framework in simulation using a real-world application in sensor networks.